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arXiv · 2311.17329

Cascade: A Platform for Delay-Sensitive Edge Intelligence

Weijia Song·Thiago Garrett·Yuting Yang·Mingzhao Liu·Edward Tremel·Lorenzo Rosa·Andrea Merlina·Roman Vitenberg·Ken Birman
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Abstract

Interactive intelligent computing applications are increasingly prevalent, creating a need for AI/ML platforms optimized to reduce per-event latency while maintaining high throughput and efficient resource management. Yet many intelligent applications run on AI/ML platforms that optimize for high throughput even at the cost of high tail-latency. Cascade is a new AI/ML hosting platform intended to untangle this puzzle. Innovations include a legacy-friendly storage layer that moves data with minimal copying and a "fast path" that collocates data and computation to maximize responsiveness. Our evaluation shows that Cascade reduces latency by orders of magnitude with no loss of throughput.

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Weijia Song, Thiago Garrett, Yuting Yang, Mingzhao Liu, Edward Tremel, Lorenzo Rosa, Andrea Merlina, Roman Vitenberg, Ken Birman. 2023-11-29. Cascade: A Platform for Delay-Sensitive Edge Intelligence. https://arxiv.org/abs/2311.17329

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